Bayesiangammareg: Double Generalized Gamma Regression Models

Fits double generalized Gamma regression models from a Bayesian perspective, where both the mean and shape parameters are modeled simultaneously using flexible link functions. The methodology is based on Cepeda-Cuervo and Urdinola (2012) <doi:10.1080/03610918.2011.600500> and extended in Cepeda-Cuervo (2026), 'Double Generalized Linear Models: Likelihood and Bayesian Methods' (ISBN: 9781041169970). The package provides parameter estimation, model fitting, and model comparison tools, including Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC).

Version: 0.1.1
Depends: R (≥ 3.1.1), mvtnorm
Published: 2026-05-22
DOI: 10.32614/CRAN.package.Bayesiangammareg
Author: Arturo Camargo-Lozano [aut, cre], Edilberto Cepeda-Cuervo [aut]
Maintainer: Arturo Camargo-Lozano <bacamargol at unal.edu.co>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.r-project.org
NeedsCompilation: no
In views: Bayesian
CRAN checks: Bayesiangammareg results

Documentation:

Reference manual: Bayesiangammareg.html , Bayesiangammareg.pdf

Downloads:

Package source: Bayesiangammareg_0.1.1.tar.gz
Windows binaries: r-devel: Bayesiangammareg_0.1.0.zip, r-release: Bayesiangammareg_0.1.0.zip, r-oldrel: Bayesiangammareg_0.1.0.zip
macOS binaries: r-release (arm64): Bayesiangammareg_0.1.0.tgz, r-oldrel (arm64): Bayesiangammareg_0.1.0.tgz, r-release (x86_64): Bayesiangammareg_0.1.0.tgz, r-oldrel (x86_64): Bayesiangammareg_0.1.0.tgz
Old sources: Bayesiangammareg archive

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